DocumentCode
2830242
Title
Notice of Retraction
Optimization system research on productive project of large-scale farms based on genetic algorithm
Author
Yu Xiao ; Shen Weizheng
Author_Institution
Eng. Coll., Northeast Agric. Univ., Harbin, China
Volume
8
fYear
2010
fDate
22-24 Oct. 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In precision Agriculture, it is a vital issue to precisely formulate the agricultural productive project, because it will affect the agricultural productive benefits. This paper uses an improved genetic algorithm to solve optimization issues of productive project of large-scale farm. We have adopted J2EE to develop management and optimization of web-based agricultural productive project, and then to fulfill optimal management of agricultural productive project. The achievement of this research will help to solve optimization issue of productive project of large-scale farms, to fulfill scientific and automation of crop productive project, to improve the optimization efficiency, and then to enhance economic and social benefits of large-scale farms. Thus it will eventually achieve the aim of precision agriculture.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In precision Agriculture, it is a vital issue to precisely formulate the agricultural productive project, because it will affect the agricultural productive benefits. This paper uses an improved genetic algorithm to solve optimization issues of productive project of large-scale farm. We have adopted J2EE to develop management and optimization of web-based agricultural productive project, and then to fulfill optimal management of agricultural productive project. The achievement of this research will help to solve optimization issue of productive project of large-scale farms, to fulfill scientific and automation of crop productive project, to improve the optimization efficiency, and then to enhance economic and social benefits of large-scale farms. Thus it will eventually achieve the aim of precision agriculture.
Keywords
Internet; Java; agricultural engineering; crops; genetic algorithms; precision engineering; project management; J2EE; Web based agricultural productive project; agricultural productive project; crop productive project; improved genetic algorithm; large-scale farm; optimization system research; precision agriculture; Agriculture; Economics; Gallium; Genetics; Maintenance engineering; Silicon; J2EE; genetic algorithm; large-scale farms; optimization management; productive project;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5620191
Filename
5620191
Link To Document